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Modeling Power of Stochastic Petri Nets for Simulation

Published online by Cambridge University Press:  27 July 2009

Peter J. Haas  and
Gerald S. Shedler
Peter J. Haas
Affiliation:
IBM Almaden Research Center San Jose, California 95120-6099
Gerald S. Shedler
Affiliation:
IBM Almaden Research Center San Jose, California 95120-6099
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Extract

Generalized semi-Markov processes and stochastic Petri nets have been proposed as general frameworks for a discrete event simulation on a countable state space. The two formal systems differ, however, with respect to the clock setting (event scheduling) mechanism, the state transition mechanism, and the form of the state space. We obtain conditions under which the marking process of a stochastic Petri net “mimics” a generalized semi-Markov process in the sense that the two processes (and their underlying general state-space Markov chains) have the same finite dimensional distributions. The results imply that stochastic Petri nets have at least the modeling power of generalized semiMarkov processes for discrete event simulation.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 2 , Issue 4 , October 1988 , pp. 435 - 459
Copyright
Copyright © Cambridge University Press 1988

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